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Tesi etd-11152015-211525


Thesis type
Tesi di laurea magistrale
Author
PARISI, CLAUDIO
URN
etd-11152015-211525
Title
Optimization of Parallel Computations on Heterogeneous GPU-Based Systems
Struttura
INFORMATICA
Corso di studi
INFORMATICA E NETWORKING
Supervisors
relatore Prof. Danelutto, Marco
correlatore Prof. Kessler, Christoph
Parole chiave
  • GPGPU
Data inizio appello
04/12/2015;
Consultabilità
Completa
Riassunto analitico
In this master thesis, we design and implement MultiStream: a solution that extends the existing data parallel skeleton library SkePU with NVIDIA CUDA Streams to overlap main memory – device memory data transfers with CUDA Kernel executions.
We show the benefits of this approach using a task-parallel framework, FastFlow, on-top of SkePU.
Finally, we compare the MultiStream extended SkePU to an ad-hoc solution to discuss the tradeoffs between the level of abstraction and the maximum achievable performance.
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